On inferences about lag effects using lag models in air pollution time-series studies
On inferences about lag effects using lag models in air pollution time-series studies
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DOI：
10.1016/j.envres.2018.12.032
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发表时间：
2019-04-01
影响因子：
8.3
通讯作者：
Lee, Jong-Tae
中科院分区：
文献类型：
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作者：
Kim, Honghyok;Lee, Jong-Tae
滞后长度的选择是空气污染时间序列研究中的一个不确定性问题。滞后模型和模型选择被广泛用于滞后效应的推断，但缺乏对两者结合的讨论。我们的目的是提供理论上的讨论滞后模型的性能，以及模型的选择对滞后效应的推断的影响。在滞后分析的背景下，讨论了基于信息标准、统计显著性、效应量和模型平均值的偏倚和模型选择。为了探索滞后模型的性能和比较模型的选择，还进行了模拟与8个PM2.5-死亡率的关系情景。应用考虑了不足滞后间隔的滞后模型（即不足滞后模型）提供了有偏估计。我们提供了模式选择的特点，并指出其陷阱在空气污染时间序列研究的滞后分析。我们还讨论了荟萃分析的局限性，它没有考虑在个别研究中应用不同的滞后模型。为了促进利用相关工具对空气污染-滞后-响应关系的探索，我们鼓励研究人员在效应估计和方差估计方面比较不同的滞后模型，并根据支持滞后-响应关系的科学知识一起报告他们喜欢的模型和竞争模型。
The choice of lag length is a matter of uncertainty in air pollution time-series studies. Lag models and model selections are widely used for inferences about lag effects, but there is lack of discussion on the integration of the two. We aimed to provide theoretical discussion on the performance of lag models, and the impact of model selections on inferences about lag effects. Bias and model selections based upon information criteria, statistical significance, effect size, and model averaging were discussed in the context of lag analysis. A simulation with eight of PM2.5-mortality relation scenarios was also conducted in order to explore the performances of lag models and to compare the model selections. The application of lag models with an insufficient lag interval taken into account (i.e. insufficient lag models) provides biased estimates. We provided features of the model selections and showed their pitfalls in lag analysis of air pollution time-series studies. We also discussed limitations of meta-analysis which fails to consider the application of different lag models in individual studies. To foster exploration on air pollution-lag-response relations with relevant tools, we encourage researchers to compare different lag models in terms of effect estimates and variance estimates, and to report their favored models and competing models together based upon scientific knowledge supporting lag-response relations.